title: Improved El Nino forecasting by cooperativity detection.
abstract: Although anomalous episodic warming of the eastern equatorial Pacific, dubbed El Niño by Peruvian fishermen, has major (and occasionally devastating) impacts around the globe, robust forecasting is still limited to about 6 mo ahead. A significant extension of the prewarning time would be instrumental for avoiding some of the worst damages such as harvest failures in developing countries. Here we introduce a unique avenue toward El Niño prediction based on network methods, inspecting emerging teleconnections. Our approach starts from the evidence that a large-scale cooperative mode--linking the El Niño basin (equatorial Pacific corridor) and the rest of the ocean--builds up in the calendar year before the warming event. On this basis, we can develop an efficient 12-mo forecasting scheme, i.e., achieve some doubling of the early-warning period. Our method is based on high-quality observational data available since 1950 and yields hit rates above 0.5, whereas false-alarm rates are below 0.1.
authors.affiliation: Institut für Theoretische Physik, Justus-Liebig-Universität Giessen, 35392 Giessen, Germany.
authors.forename: Josef
authors.initials: J
authors.lastname: Ludescher
authors.forename: Avi
authors.initials: A
authors.lastname: Gozolchiani
authors.forename: Mikhail I
authors.initials: MI
authors.lastname: Bogachev
authors.forename: Armin
authors.initials: A
authors.lastname: Bunde
authors.forename: Shlomo
authors.initials: S
authors.lastname: Havlin
authors.forename: Hans Joachim
authors.initials: HJ
authors.lastname: Schellnhuber
mesh_terms: D000465:Algorithms; D059000:El Nino-Southern Oscillation; D005544:Forecasting / Q000379:methods*; D010140:Pacific Ocean; D012680:Sensitivity and Specificity; D013696:Temperature; D013997:Time Factors
keywords: ENSO; climate; cross-correlations; dynamic networks; spring barrier